@inproceedings{f8c5fa58557b4bc698b862e32c13482e,
title = "Exploiting global impact ordering for higher throughput in selective search",
abstract = "We investigate potential benefits of exploiting a global impact ordering in a selective search architecture. We propose a generalized, ordering-aware version of the learning-to-rank-resources framework [9] along with a modified selection strategy. By allowing partial shard processing we are able to achieve a better initial trade-off between query cost and precision than the current state of the art. Thus, our solution is suitable for increasing query throughput during periods of peak load or in low-resource systems.",
keywords = "Global ordering, Selective search, Shard selection",
author = "Micha{\l} Siedlaczek and Juan Rodriguez and Torsten Suel",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 41st European Conference on Information Retrieval, ECIR 2019 ; Conference date: 14-04-2019 Through 18-04-2019",
year = "2019",
doi = "10.1007/978-3-030-15719-7_2",
language = "English (US)",
isbn = "9783030157180",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "12--19",
editor = "Claudia Hauff and Norbert Fuhr and Leif Azzopardi and Djoerd Hiemstra and Benno Stein and Philipp Mayr",
booktitle = "Advances in Information Retrieval - 41st European Conference on IR Research, ECIR 2019, Proceedings",
}